Significant mitral regurgitation (MR) is a common ailment among patients with severe aortic stenosis (AS), and the management of these patients is challenging because the aortic and mitral valves are interdependent. Transcatheter aortic valve replacement (TAVR) can significantly reduce AS symptoms in high-risk patients; however, this procedure displaces the aortic-mitral curtain delineating the two valves, and may consequently have unexpected and adverse effects on mitral valve function. Studies have shown that MR severity is improved in approximately 50% of patients following TAVR, but unchanged or even worsened in others. The objective of this study is to develop a coupled mitral-aortic-left ventricle (LV) computational modeling framework to investigate the biomechanics involved in TAVR in patients with concomitant MR, in order to improve our understanding of mitral-aortic coupling and predict the effects of TAVR on MR severity. To achieve this goal, mitral-aortic-LV coupling computational models will be developed to investigate pre-TAVR hemodynamics, and validated against clinical 3D echocardiogram (3DE) and Cardiac Magnectic Resonance (CMR) image data (Aim 1). The models will be used to simulate TAVR device deployment to investigate the impacts of TAVR on the mitral valve and MR severity, and validated against post-TAVR 3DE and CMR data (Aim 2). Through parametric study, the optimal TAVR device and deployment strategies to improve patient outcomes will be investigated through the validated computational methods of Aims 1 and 2 (Aim 3). The results from this study may provide scientific rationale to improve the current clinical decision-making process, including patient and TAVR device selection, TAVR device positioning and deployment strategy, and the selection of intervention methods for MR improvement.